machine-learning boxes, be compliant with the company’s policy, drive the ROI engine in that bot’s chips and justify the expense. Not only that, it was searching for the best
deal via the dynamic contract the corpora- tion had signed up to with travel suppliers. NDC was now in full swing. The Amazon for flights was tight for airlines. But for buyers, it was an incredible new world. The AI engine had also selected all the ancillary services that Chris had come to expect and processed them automatically within policy. “You’re booked on the 3pm flight, Chris.
Thank you for being compliant. I’ve made all your arrangements end-to-end based on your personal profile, and real-time travel in- formation,” said the smart virtual assistant. Suddenly his desktop and smartphone
exploded in a cacophony of sound. It re- minded him of the chiming of Big Ben at midnight. This always happened now. Ev- erything bloody synchronising. His calendar instantly updating, itineraries then posted to his smartphone, risk assessments at the ready, expense forms lodged. Payments made and loyalty cards updated, all chiming: ‘I’m done’ one after the other. What Chris didn’t like was all the proac-
tive recommendations it made based on what he liked: restaurants he should take clients to, or where to conduct his morning run. It assumed way too much about him. It was spooky; in fact it knew too much. Sodding Big Data. He was aware he would get it all again for this Hong Kong trip. Kirsty called it the ‘power app’. It managed everything end-to-end, door-to-door. Chris
wasn’t sure it was a good term; yes it was seamless, but hyper-efficient only up to the point of calamity, he thought. The last trip he had ordered through the virtual assistant to Rome was a balls-up. It booked him in as being a vegan and needing wheelchair access – no one knew why – but it took the IT team a day to unpick. When he came to think about it, there
didn’t seem to be much choice these days as a business traveller, a bit like British politics in 2030. Also, travel managers had all the control. They just served up a clever illusion of so-called choice to executives, a bit like chicken or fish on a flight a decade ago, to make you feel like you have more options
“Travel managers appeared like Greek gods of old, peering down on their human subjects”
than you really do. At the end of the day travel policy dictated everything with a technocratic iron fist. Chris also blamed Kirsty’s travel manage-
ment company. They had evolved into an intelligent hub for all the data that was being generated from a myriad of sources – travel suppliers, executives themselves, corporate finance, human resources, social media and security experts. They provided travel
managers like Kirsty with a customisable, smart dashboard that connected all the data up and provided all the information needed for refining programme and policy. Every travelling executive could also be
tracked in real-time. Powerful yes, Chris thought, but it allowed travel managers to act as if they were playing, well, a trumped- up game of corporate chess. Travel policy dictated the rules. The pawns were the executives. The travel managers, in his mind, appeared like the Greek gods of old, peering down on their human subjects. Apparently, Kirsty was now trialling a
new virtual and augmented reality travel management suite, software and hardware that had been the domain of video gamers. It was now coming into the world of managed travel. With this you could get live police updates on terrorism, weather reports on the predicted path of a hurricane, matched to where your executive travellers are and how they would be affected. Yet those long in the tooth like Chris remembered an era when you could cir- cumvent the travel-gods and be a maverick. Not anymore. It was total lockdown. Digital payment systems made sure of that. One digital wallet, one virtual credit card per trip and all in- visible payments via mobile or direct. Also, blockchain was starting to power everything from charges
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